tesseract_robotics.tesseract_collision¶
Collision detection managers and contact queries.
Contact Managers¶
DiscreteContactManager¶
Checks collision at a single configuration.
Python
from tesseract_robotics.tesseract_collision import DiscreteContactManager
# Get from environment
manager = env.getDiscreteContactManager()
# Clone for thread safety
my_manager = manager.clone()
# Set collision objects state
my_manager.setCollisionObjectsTransform(link_transforms)
# Run collision check — fills ContactResultMap
result_map = ContactResultMap()
my_manager.contactTest(result_map, request)
ContinuousContactManager¶
Checks collision along swept motion.
Python
from tesseract_robotics.tesseract_collision import ContinuousContactManager
# Get from environment
manager = env.getContinuousContactManager()
# Clone for thread safety
my_manager = manager.clone()
# Set start and end transforms
my_manager.setCollisionObjectsTransform(
link_transforms_start,
link_transforms_end
)
# Run continuous collision check
result_map = ContactResultMap()
my_manager.contactTest(result_map, request)
Contact Request¶
Configure what contacts to find.
Python
from tesseract_robotics.tesseract_collision import (
ContactRequest, ContactTestType
)
request = ContactRequest()
request.type = ContactTestType.ALL # find all contacts
# Alternatively
request.type = ContactTestType.FIRST # stop at first contact
request.type = ContactTestType.CLOSEST # only closest contact
request.type = ContactTestType.LIMITED # up to max contacts
| ContactTestType | Description |
|---|---|
FIRST |
Stop at first contact found |
CLOSEST |
Only return closest contact |
ALL |
Return all contacts |
LIMITED |
Return up to N contacts |
Contact Results¶
ContactResult¶
Single contact between two objects.
Python
from tesseract_robotics.tesseract_collision import ContactResult, ContactResultVector
# ContactResultMap is a nested map (link_a → link_b → list[ContactResult]).
# Flatten it to iterate individual contacts.
result_vector = ContactResultVector()
result_map.flattenMoveResults(result_vector) # or flattenCopyResults()
for contact in result_vector:
print(f"Contact: {contact.link_names[0]} <-> {contact.link_names[1]}")
print(f" Distance: {contact.distance}")
print(f" Point A: {contact.nearest_points[0]}")
print(f" Point B: {contact.nearest_points[1]}")
print(f" Normal: {contact.normal}")
| Attribute | Type | Description |
|---|---|---|
link_names |
tuple[str, str] |
Colliding link names |
distance |
float |
Signed distance (negative = penetration) |
nearest_points |
tuple[np.array, np.array] |
Contact points |
normal |
np.array |
Contact normal (A to B) |
cc_time |
tuple[float, float] |
Continuous collision times |
ContactResultMap¶
Nested map: link_a → link_b → list[ContactResult]. Exposes size(),
empty(), count(), clear(), getSummary(), and
flattenCopyResults() / flattenMoveResults() for iteration.
Python
from tesseract_robotics.tesseract_collision import ContactResultMap
result_map = ContactResultMap()
manager.contactTest(result_map, request)
print(f"{result_map.size()} contact pairs")
print(result_map.getSummary())
ContactResultVector¶
Flat list of ContactResult. Use this for iteration.
Python
from tesseract_robotics.tesseract_collision import ContactResultVector
all_contacts = ContactResultVector()
result_map.flattenMoveResults(all_contacts) # or flattenCopyResults to keep map data
for contact in all_contacts:
print(contact.distance, contact.link_names)
Configuration¶
CollisionCheckConfig¶
Configure collision checking behavior.
Python
from tesseract_robotics.tesseract_collision import CollisionCheckConfig
config = CollisionCheckConfig()
config.contact_request = request
config.longest_valid_segment_length = 0.01 # for continuous
ContactManagerConfig¶
Configure contact manager settings.
Python
from tesseract_robotics.tesseract_collision import ContactManagerConfig
config = ContactManagerConfig()
config.margin_data.setDefaultCollisionMargin(0.025)
config.margin_data.setPairCollisionMargin("link_a", "link_b", 0.05)
Convex Mesh Generation¶
Generate convex hulls for collision.
Python
from tesseract_robotics.tesseract_collision import makeConvexMesh
# From vertices
vertices = [np.array([x, y, z]) for ...]
convex = makeConvexMesh(vertices)
Collision Evaluator Types¶
Used with trajectory optimization.
Python
from tesseract_robotics.tesseract_collision import CollisionEvaluatorType
CollisionEvaluatorType.DISCRETE # single config
CollisionEvaluatorType.LVS_DISCRETE # interpolated discrete
CollisionEvaluatorType.LVS_CONTINUOUS # swept volume
CollisionEvaluatorType.CONTINUOUS # continuous
Usage Example¶
Python
from tesseract_robotics.tesseract_collision import (
ContactRequest, ContactTestType, ContactResultMap, ContactResultVector
)
# Setup
manager = env.getDiscreteContactManager().clone()
request = ContactRequest()
request.type = ContactTestType.ALL
# Set state
env.setState({"joint_1": 0.0, "joint_2": 0.0})
state = env.getState()
manager.setCollisionObjectsTransform(state.link_transforms)
# Check collision
results = ContactResultMap()
manager.contactTest(results, request)
# Process results
if not results.empty():
contacts = ContactResultVector()
results.flattenMoveResults(contacts)
for c in contacts:
if c.distance < 0:
print(f"Penetration: {c.link_names} depth={-c.distance:.4f}")
Auto-generated API Reference¶
Bases: Enum
Bases: Enum
Bases: Enum
Python
setCollisionMarginData(collision_margin_data: 'tesseract_common::CollisionMarginData') -> None
Python
addCollisionObject(name: str, mask_id: int, shapes: Sequence['tesseract_geometry::Geometry'], shape_poses: Sequence['Eigen::Transform<double, 3, 1, 0>'], enabled: bool = True) -> bool
Python
getCollisionObjectGeometriesTransforms(name: str) -> list['Eigen::Transform<double, 3, 1, 0>']
Python
setCollisionObjectsTransformCast(name: str, pose1: 'Eigen::Transform<double, 3, 1, 0>', pose2: 'Eigen::Transform<double, 3, 1, 0>') -> None
Create a ConvexMesh from a Mesh using bullet's convex hull algorithm